COMMUNICATION METHOD AND APPARATUS
    11.
    发明公开

    公开(公告)号:US20230337194A1

    公开(公告)日:2023-10-19

    申请号:US18340186

    申请日:2023-06-23

    CPC classification number: H04W72/04

    Abstract: A communication method is provided, including: A second device receives policy related information from M first devices; the second device obtains transmission decisions of the M first devices based on the policy related information by using a second neural network; the second device updates the second neural network based on reward information, and sends, to the M first devices, information for updating a first neural network, and the third device obtains second update parameter information of the first neural network based on the first update parameter information of the first neural network of the M first devices, and sends the second update parameter information of the first neural network to the M first devices, so that the first device may update the first neural network. The second update parameter information is obtained in a training process, so that training overheads can be reduced.

    Channel Encoding Method and Apparatus in Wireless Communications

    公开(公告)号:US20200092040A1

    公开(公告)日:2020-03-19

    申请号:US16693906

    申请日:2019-11-25

    Abstract: This application provides a channel encoding method and apparatus in wireless communications. The method includes: performing CRC encoding on A to-be-encoded information bits, to obtain a first bit sequence, where the first bit sequence includes L CRC bits and A information bits; performing a interleaving operation on the first bit sequence, to obtain a second bit sequence, where a first interleaving sequence used for the interleaving operation is obtained based on a system-supported maximum-length interleaving sequence with the length of Kmax+L, and Kmax is a maximum information bit quantity corresponding to the maximum-length interleaving sequence ad a preset rule, and a length of the first interleaving sequence is equal to A+L. Therefore, during distributed CRC encoding, when an information bit quantity is less than the maximum information bit quantity, an interleaving sequence required for completing an interleaving process is obtained based on the system-supported maximum-length interleaving sequence.

    Method For Constructing Sequence Of Polar Codes And Apparatus

    公开(公告)号:US20180351699A1

    公开(公告)日:2018-12-06

    申请号:US16058118

    申请日:2018-08-08

    Abstract: Embodiments of this application provide a method and an apparatus for constructing a sequence of polar codes. In an implementation, a tectonic sequence P′ is read from a tectonic sequence P, where the length of the tectonic sequence P′ is an encoding length M and the length of the tectonic sequence P is N. The tectonic sequence P′ is demapped to a reliability ranking sequence Q′ based on a rate matching rule, and K elements that have largest reliability values is read from the reliability ranking sequence Q′, to obtain an information bit sequence number set A.

    MODEL TRAINING METHOD AND COMMUNICATION APPARATUS

    公开(公告)号:US20240296345A1

    公开(公告)日:2024-09-05

    申请号:US18663656

    申请日:2024-05-14

    CPC classification number: G06N3/098

    Abstract: A model training method includes performing, by an ith device in a kth group of devices, n*M times of model training. The ith device completes a model parameter exchange with at least one other device in the kth group of devices every M times of model training, M is a quantity of devices in the kth group of devices, M is greater than or equal to 2, and n is an integer. The model training method also includes sending, by the ith device, a model Mi,n*M to a target device. The model Mi,n*M is obtained by the ith device by completing the n*M times of model training.

    DATA TRANSMISSION METHOD AND RELATED APPARATUS

    公开(公告)号:US20240089742A1

    公开(公告)日:2024-03-14

    申请号:US18514066

    申请日:2023-11-20

    CPC classification number: H04W16/18 H04W72/50

    Abstract: A first machine learning model is deployed in a first communication apparatus, and a second machine learning model is deployed in a second communication apparatus. First information is obtained that carries indication information of both a first transmission resource and a second transmission resource, wherein the first transmission resource is for the first communication apparatus to transmit a first output of the first machine learning model to the second communication apparatus, and wherein the second transmission resource is for the first communication apparatus to receive first feedback data that is from the second communication apparatus. The first feedback data includes a first gradient, wherein the first gradient is for updating the first machine learning model. The first communication apparatus transmits the first output to the second communication apparatus on the first transmission resource.

    DECISION-MAKING METHOD FOR AGENT ACTION AND RELATED DEVICE

    公开(公告)号:US20230032176A1

    公开(公告)日:2023-02-02

    申请号:US17964233

    申请日:2022-10-12

    Abstract: A decision-making method for an agent action and a related device are provided and are used in the field of communication technologies. The method includes: a first agent processes first state information obtained from an environment through a first model, to obtain a first cooperation message; the first agent sends the first cooperation message to at least one second agent; the first agent receives second cooperation message sent by the at least one second agent; the first agent processes the first cooperation message and the second cooperation message through a second model, to obtain a first cooperation action performed by the first agent, where the second cooperation message is sent by the at least one second agent.

    AGENT DECISION-MAKING METHOD AND APPARATUS

    公开(公告)号:US20220391731A1

    公开(公告)日:2022-12-08

    申请号:US17891401

    申请日:2022-08-19

    Abstract: This application provides an agent decision-making method and an apparatus, to improve decision-making performance of an agent. The method is applied to a communications system. The communications system includes at least two function modules. The at least two function modules include a first function module and a second function module, where the first function module is configured with a first agent, and the second function module is configured with a second agent. The method further includes the first agent obtaining related information of the second agent, and makes a decision on the first function module based on the related information of the second agent.

    POLAR CODE ENCODING/DECODING METHOD AND ENCODING/DECODING APPARATUS

    公开(公告)号:US20200028524A1

    公开(公告)日:2020-01-23

    申请号:US16556920

    申请日:2019-08-30

    Abstract: Embodiments of polar encoding/decoding methods and apparatuses are described. CRC encoding is performed on an information block to obtain a CRC encoded block with a length of B, where a CRC length is Lcrc, an information block length is K, and B=K+Lcrc. The CRC encoded block is interleaved. Lpc CRC bits in the interleaved encoded block are located between bits of the information block. Each CRC bit of the Lpc CRC bits is located after all bits checked by using the CRC bit. Lpc is an integer greater than 0 and less than Lcrc. The interleaved encoded block is mapped to information bits. A frozen bit is set to an agreed fixed value. Polar encoding is performed on the information bits and the frozen bit to obtain a polar encoded codeword to improve performance of a CA-polar code.

    COMMUNICATION METHOD AND COMMUNICATION APPARATUS

    公开(公告)号:US20250106599A1

    公开(公告)日:2025-03-27

    申请号:US18969862

    申请日:2024-12-05

    Abstract: A method includes: obtaining first semantic information corresponding to data; converting the first semantic information into second semantic information, where the second semantic information belongs to common semantic information, and the common semantic information is a unified description of same semantics that is provided by different devices; and sending the second semantic information. Based on the method provided in this application, when a semantic extraction model of a transmit device and a semantic understanding model of a receive device are not jointly trained, accuracy of semantic communication between the transmit device and the receive device may be ensured by converting local semantic information into common semantic information.

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